Occlusal comparison of hand-articulation versus digital articulation in orthognathic surgery

The aim of the present study was to develop measurement methods to evaluate occlusal differences in digitally-articulated and hand-articulated models in final occlusal planning for orthognathic surgery. A total of 10 (five class II and five class III) previously treated orthognathic cases were analysed by three oral and maxillofacial surgeon investigators, creating a total of thirty cases. Investigators used physical models to create a preferred hand-held final occlusion, which were then scanned and saved utilising a Trios 3® scanner (3Shape). Models were digitally disarticulated and sent back to investigators after a period of at least a month for digital articulation. Novel measurements of dental roll, pitch, and translational differences were performed by an independent engineer using Materialise 3-Matic® software. Statistical analysis was used to evaluate translational differences, the effect of deformity, and inter-investigator variation. A mean (SD) translational difference of 1.58 mm (1.14) mm was seen between the thirty digital and hard-articulated cases analysed. Minimal difference was seen in roll and pitch between hand articulation and digital articulation. A significant translational difference was seen in class III cases compared with class II (p = 0.0006) but not in roll or pitch. There was no significant difference seen between investigators related to translation (p = 0.18), roll (p = 0.09), or pitch (p = 0.17). Digital articulation yielded similar results to hand held in this pilot study. Using measurement techniques described in larger cohorts, its accuracy can be validated using currently available technology.     

Preoperative Ozaki technique measures on tridimensional engineered root

BackgroundThe aortic valve neocuspidalization (AVNeo) is an innovative surgical technique aiming at the reconstruction of the aortic valve using autologous pericardium. One of the main criticisms to AVNeo is the longer duration of the aortic clamping time (ACT) as compared to standard aortic valve replacement due to the sizing of the valve neocusps.MethodsWe retrospectively enrolled 30 consecutives patients underwent AVNeo. For each patient we developed a 3D aortic root model (ARM) based on CT-scan datasets. We retrospectively compared the leaflets measurements performed during surgery with those obtained on the corresponding ARMs.ResultsIn 100% of cases no difference between the in vitro and in vivo measurements exceeded the acceptable error limit of 2 ?mm. The correlation of each single in vitro versus in vivo measurements demonstrates a strong coincidence between the two different methods of sizing (r ?> ?0,9, p ?< ?.0001). By analyzing the data considering the annulus perimeter and not the single cusp size, the perfect coincidence was to be found in 89.9% with a slight acceptable discrepancy (2 ?mm on total) in the remaining 10.1%.Conclusions3D-ARMs, printed from CT-scan, represent a reproducible process to obtain overlapping cusp sizes compared to those measured in-vivo, possibly reducing the ACT.     

Augmented reality guided condylectomy

An accurate transfer of a 3D virtual planned proportional condylectomy to the patient is challenging due to the limited surgical access. A new clinical workflow that uses augmented reality to assist a condylectomy is presented step-by-step. This AR-based approach has the potential to be implemented in the clinical setting routinely.     

What information can we gain from performing adaptive radiotherapy of head and neck cancer patients from the past 10 years?

The aim of the review was to present the current literature status about replanning regarding anatomical and dosimetric changes in the target and OARs in the head and neck region during radiotherapy, to discuss and to analyze factors influencing the decision for adaptive radiotherapy of head and neck cancer patients. Significant progress has been made in head and neck patients’ evaluation and qualification for adapted radiotherapy over the past ten years. Many factors leading to anatomical and dosimetric changes during treatment have been identified. Based on the literature, the most common factors triggering re-plan are weight loss, tumor and nodal changes, and parotid glands shrinkage. The fluctuations in dose distribution in the clinical area are significant predictive factors for patients’ quality of life and the possibility of recovery. It has been shown that re-planning influence clinical outcomes: local control, disease free survival and overall survival. Regarding literature studies, it seems that adaptive radiotherapy would be the most beneficial for tumors of immense volume or those in the nearest proximity of the OARs. All researchers agree that the timing of re-planning is a crucial challenge, and there are still no clear consensus guidelines for time or criteria of re-planning. Nowadays, thanks to significant technological progress, the decision is mostly made based on observation and supported with IGRT verification. Although further research is still needed, adaptive strategies are evolving and now became the state of the art of modern radiotherapy.     

Optimal parameter selection problem with application to the synchronization of delivery cycles in a supply chain with Wiener process

In this paper, we use optimal parameter selection technique to develop two models involving single‐vendor–multiple‐buyer supply chain, which are called the dynamic independent optimization (DIO) model and the dynamic synchronized cycles (DSC) model, respectively. These models are, respectively, similar to the traditional static independent policy model and the traditional static synchronized cycle model, except that the deterministic demands of the buyers in the above two static models are now being replaced by the stochastic demands satisfying a Wiener process, which have more real‐life applications. Similar to the above static synchronized cycles model, the synchronization of the supply chain in our DSC model is also achieved by scheduling the delivery days of the buyers and coordinating them with the vendor's production cycle. Finding the optimal expected system costs of the DIO model and the DSC model involves solving optimal parameter selection problems governed by ordinary differential equations, whose final times are continuous decision variables and discrete decision variables, respectively. Computational methods have been developed for solving these problems. Numerical results show that the coordinated policy is better than the independent optimization policy, in terms of minimizing the expected system cost of the entire supply chain. Sensitivity analysis is performed to test the effect of changing the cost coefficients and the value on the performances of these models, where is the ratio of the total mean demand rate of all the buyers over the vendor's production rate.     

Three-dimensional soft tissue prediction in orthognathic surgery: a clinical comparison of Dolphin,ProPlan CMF,and probabilistic finite element modelling

Three-dimensional surgical planning is used widely in orthognathic surgery. Although numerous computer programs exist, the accuracy of soft tissue prediction remains uncertain. The purpose of this study was to compare the prediction accuracy of Dolphin, ProPlan CMF, and a probabilistic finite element method (PFEM). Seven patients (mean age 18 years; five female) who had undergone Le Fort I osteotomy with preoperative and 1-year postoperative cone beam computed tomography (CBCT) were included. The three programs were used for soft tissue prediction using planned and postoperative maxillary position, and these were compared to postoperative CBCT. Accurate predictions were obtained with each program, indicated by root mean square distances: RMS_Dolphin = 1.8 ± 0.8 mm, RMS_ProPlan = 1.2 ± 0.4 mm, and RMS_PFEM = 1.3 ± 0.4 mm. Dolphin utilizes a landmark-based algorithm allowing for patient-specific bone-to-soft tissue ratios, which works well for cephalometric radiographs but has limited three-dimensional accuracy, whilst ProPlan and PFEM provide better three-dimensional predictions with continuous displacements. Patient or population-specific material properties can be defined in PFEM, while no soft tissue parameters are adjustable in ProPlan. Important clinical considerations are the topological differences between predictions due to the three algorithms, the non-negligible influence of the mismatch between planned and postoperative maxillary position, and the learning curve associated with sophisticated programs like PFEM.